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Recommendation Systems in Software Engineering by Martin P. Robillard (English)
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- ISBN-13
- 9783642451348
- Book Title
- Recommendation Systems in Software Engineering
- ISBN
- 9783642451348
- Subject Area
- Computers
- Publication Name
- Recommendation Systems in Software Engineering
- Publisher
- Springer Berlin / Heidelberg
- Item Length
- 9.3 in
- Subject
- Software Development & Engineering / General, Management Information Systems, System Administration / Storage & Retrieval
- Publication Year
- 2014
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Weight
- 346.1 Oz
- Item Width
- 6.1 in
- Number of Pages
- Xiii, 562 Pages
關於產品
Product Identifiers
Publisher
Springer Berlin / Heidelberg
ISBN-10
3642451349
ISBN-13
9783642451348
eBay Product ID (ePID)
176376925
Product Key Features
Number of Pages
Xiii, 562 Pages
Language
English
Publication Name
Recommendation Systems in Software Engineering
Publication Year
2014
Subject
Software Development & Engineering / General, Management Information Systems, System Administration / Storage & Retrieval
Type
Textbook
Subject Area
Computers
Format
Hardcover
Dimensions
Item Weight
346.1 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2014-931203
Dewey Edition
23
Reviews
" The book is a perfect starting point of study for graduate students of software engineering, especially when specializing in recommendation. It is highly recommended also to software professionals seeking to learn what are the possible future directions of their professional field. The book is impressive. [...] I highly recommend this book to software engineering students, professionals, experts, and other interested readers." P. Navrat, ACM Computing Reviews, November 2014, " The book is a perfect starting point of study for graduate students of software engineering, especially when specializing in recommendation. It is highly recommended also to software professionals seeking to learn what are the possible future directions of their professional field. The book is impressive. [...] I highly recommend this book to software engineering students, professionals, experts, and other interested readers." P. Navrat, ACM Computing Reviews, November 2014
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
005.1
Table Of Content
1 An Introduction to Recommendation Systems in Software Engineering.- Part I Techniques.- 2 Basic Approaches in Recommendation Systems.- 3 Data Mining.- 4 Recommendation Systems in-the-Small.- 5 Source Code Based Recommendation Systems.- 6 Mining Bug Data.- 7 Collecting and Processing Interaction Data for Recommendation Systems.- 8 Developer Profiles for Recommendation Systems.- 9 Recommendation Delivery.- Part II Evaluation.- 10 Dimensions and Metrics for Evaluating Recommendation Systems.- 11 Benchmarking.- 12 Simulation.- 13 Field Studies.- Part III Applications.- 14 Reuse-Oriented Code Recommendation Systems.- 15 Recommending Refactoring Operations in Large Software Systems.- 16 Recommending Program Transformations.- 17 Recommendation Systems in Requirements Discovery.- 18 Changes, Evolution and Bugs.- 19 Recommendation Heuristics for Improving Product Line Configuration Processes.
Synopsis
With the growth of public and private data stores and the emergence of off-the-shelf data-mining technology, recommendation systems have emerged that specifically address the unique challenges of navigating and interpreting software engineering data. This book collects, structures and formalizes knowledge on recommendation systems in software engineering. It adopts a pragmatic approach with an explicit focus on system design, implementation, and evaluation. The book is divided into three parts: "Part I - Techniques" introduces basics for building recommenders in software engineering, including techniques for collecting and processing software engineering data, but also for presenting recommendations to users as part of their workflow. "Part II - Evaluation" summarizes methods and experimental designs for evaluating recommendations in software engineering. "Part III - Applications" describes needs, issues and solution concepts involved in entire recommendation systems for specific software engineering tasks, focusing on the engineering insights required to make effective recommendations. The book is complemented by the webpage rsse.org/book, which includes free supplemental materials for readers of this book and anyone interested in recommendation systems in software engineering, including lecture slides, data sets, source code, and an overview of people, groups, papers and tools with regard to recommendation systems in software engineering. The book is particularly well-suited for graduate students and researchers building new recommendation systems for software engineering applications or in other high-tech fields. It may also serve as the basis for graduate courses on recommendation systems, applied data mining or software engineering. Software engineering practitioners developing recommendation systems or similar applications with predictive functionality will also benefit from the broad spectrum of topics covered., This book surveys and analyzes information on recommendation systems in software engineering, in separate sections on Techniques, Evaluation and Applications. A supplemental website offers additional material, including lecture slides, source code and more., 1 An Introduction to Recommendation Systems in Software Engineering.- Part I Techniques.- 2 Basic Approaches in Recommendation Systems.- 3 Data Mining.- 4 Recommendation Systems in-the-Small.- 5 Source Code Based Recommendation Systems.- 6 Mining Bug Data.- 7 Collecting and Processing Interaction Data for Recommendation Systems.- 8 Developer Profiles for Recommendation Systems.- 9 Recommendation Delivery.- Part II Evaluation.- 10 Dimensions and Metrics for Evaluating Recommendation Systems.- 11 Benchmarking.- 12 Simulation.- 13 Field Studies.- Part III Applications.- 14 Reuse-Oriented Code Recommendation Systems.- 15 Recommending Refactoring Operations in Large Software Systems.- 16 Recommending Program Transformations.- 17 Recommendation Systems in Requirements Discovery.- 18 Changes, Evolution and Bugs.- 19 Recommendation Heuristics for Improving Product Line Configuration Processes.
LC Classification Number
QA76.758
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